起重运输机械Issue(21)：67-74,8.
自动化仓库堆垛机故障检测与诊断技术研究
周奇才 1潘金海 1王雨杨 1李宏亮2
作者信息
- 1. 同济大学机械与能源工程学院 上海 201804
- 2. 上海精星仓储设备工程有限公司 上海 201800
- 折叠
摘要
Abstract
For common stacker faults,a fault-detection system based on an LSTM-Self-Attention diagnostic model was constructed,and the model's detection performance was evaluated by acquiring vibration signals generated during stacker operation.Test results demonstrate that the diagnostic accuracy of the proposed method reaches 94.87%,enabling fault diagnosis and identification on the stacker state data set and providing a technical basis and reference for future on-line fault detection of stackers.关键词
堆垛机/故障检测/长短期记忆网络/自注意力机制Key words
stacker/fault detection/long short-term memory network/Self-attention mechanism分类
建筑与水利引用本文复制引用
周奇才,潘金海,王雨杨,李宏亮..自动化仓库堆垛机故障检测与诊断技术研究[J].起重运输机械,2025,(21):67-74,8.
